| { | |
| "name": "SoundSlayerAI", | |
| "description": "An innovative project for music-related tasks utilizing pyannote-audio library", | |
| "datasets": \[ | |
| "Fhrozen/AudioSet2K22", | |
| "Chr0my/Epidemic_sounds", | |
| "ChristophSchuhmann/lyrics-index", | |
| "Cropinky/rap_lyrics_english", | |
| "tsterbak/eurovision-lyrics-1956-2023", | |
| "brunokreiner/genius-lyrics", | |
| "google/MusicCaps", | |
| "ccmusic-database/music_genre", | |
| "Hyeon2/riffusion-musiccaps-dataset", | |
| "SamAct/autotrain-data-musicprompt", | |
| "Chr0my/Epidemic_music", | |
| "juliensimon/autonlp-data-song-lyrics", | |
| "Datatang/North_American_English_Speech_Data_by_Mobile_Phone_and_PC", | |
| "Chr0my/freesound.org", | |
| "teticio/audio-diffusion-256", | |
| "KELONMYOSA/dusha_emotion_audio", | |
| "Ar4ikov/iemocap_audio_text_splitted", | |
| "flexthink/ljspeech", | |
| "mozilla-foundation/common_voice_13_0", | |
| "facebook/voxpopuli", | |
| "SocialGrep/one-million-reddit-jokes", | |
| "breadlicker45/human-midi-rlhf", | |
| "breadlicker45/midi-gpt-music-small", | |
| "projectlosangeles/Los-Angeles-MIDI-Dataset", | |
| "huggingartists/epic-rap-battles-of-history", | |
| "SocialGrep/one-million-reddit-confessions", | |
| "shahules786/prosocial-nsfw-reddit", | |
| "Thewillonline/reddit-sarcasm", | |
| "autoevaluate/autoeval-eval-futin\_\_guess-vi-4200fb-2012366606", | |
| "lmsys/chatbot_arena_conversations", | |
| "mozilla-foundation/common_voice_11_0", | |
| "mozilla-foundation/common_voice_4_0" | |
| \], | |
| "library": "pyannote-audio", | |
| "metrics": \[ | |
| "accuracy", | |
| "bertscore", | |
| "BLEU", | |
| "BLEURT", | |
| "brier_score", | |
| "character" | |
| \], | |
| "language": "English", | |
| "usage": \[ | |
| "Install the required dependencies by running pip install pyannote-audio.", | |
| "Import the necessary modules from the 'pyannote.audio' package to access the desired functionalities.", | |
| "Load the audio data or use the provided datasets to perform tasks such as audio segmentation, speaker diarization, music transcription, and more.", | |
| "Apply the appropriate algorithms and models from the 'pyannote.audio' library to process and analyze the audio data.", | |
| "Evaluate the results using the specified metrics, such as accuracy, bertscore, BLEU, BLEURT, brier_score, and character.", | |
| "Iterate and refine your approach to achieve the desired outcomes for your music-related tasks." | |
| \], | |
| "license": "Openrail", | |
| "contributions": "Contributions to SoundSlayerAI are welcome! If you have any ideas, bug fixes, or enhancements, feel free to submit a pull request or open an issue on the GitHub repository.", | |
| "contact": "\[or4cl3ai@gmail.com\]" | |
| } |